{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import mpl_toolkits.axisartist as AA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = np.genfromtxt(\"IgnSolution.dat\", dtype=str)\n",
    "Header = (data[0,:]).tolist()\n",
    "solTchem = (data[1:,:]).astype(np.float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def makefigure(x, y1, y2, y3, y4, info, fs_label=16, fs_tick=14, figure_name='TempDensVelPFR' ):\n",
    "    \n",
    "    label1 = info['label1']['label']\n",
    "    label2 = info['label2']['label']\n",
    "    label3 = info['label3']['label']\n",
    "    label4 = info['label4']['label']\n",
    "    \n",
    "    ylabel1 = label1 + info['label1']['units']\n",
    "    ylabel2 = info['label2']['units']\n",
    "    \n",
    "    fig = plt.figure()\n",
    "#     host = AA.Axes(fig, [0.1, 0.1, 0.8, 0.8]) \n",
    "#     fig.add_axes(host)\n",
    "    host = fig.add_axes([0.1, 0.1, 0.8, 0.8]) \n",
    "    par1 = host.twinx()\n",
    "\n",
    "    host.set_xlabel(\"Time [s]\",fontsize=fs_label)\n",
    "    host.set_ylabel(ylabel1,fontsize=fs_label)\n",
    "    par1.set_ylabel(ylabel2,fontsize=fs_label)\n",
    "\n",
    "    p1 = host.plot(x, y1,'k-', label=label1)\n",
    "    p2 = par1.plot(x, y2,'b-', label=label2)\n",
    "    p3 = par1.plot(x, y3,'g-', label=label3)\n",
    "    p4 = par1.plot(x, y4,'-',color='r',label=label4)\n",
    "\n",
    "    host.set_yticks([1000,1500,2000,2500])\n",
    "    loc_x = info['loc_x']\n",
    "    loc_y = info['loc_y']\n",
    "    \n",
    "    par1.set_xlim(info['xlim'])\n",
    "\n",
    "    # added these three lines\n",
    "    lns = p1+p2+p3+p4\n",
    "    labs = [l.get_label() for l in lns]\n",
    "    host.legend(lns, labs, bbox_to_anchor=(loc_x, loc_y),fontsize=fs_tick,frameon=False)\n",
    "    \n",
    "    inset = fig.add_axes([info['inset_x1'], info['inset_y1'], info['inset_x2'], info['inset_y2']]) \n",
    "    inset.plot(x, y1,'k.-')\n",
    "    inset.set_yticks([])\n",
    "    par2 = inset.twinx()\n",
    "    par2.set_yticks([])\n",
    "    par2.plot(x, y2,'b.-')\n",
    "    par2.plot(x, y3,'g.-')\n",
    "    par2.plot(x, y4,'.-',color='r')\n",
    "    inset.set_xlim(info['xlim2'])\n",
    "    for tick in host.xaxis.get_major_ticks()+host.yaxis.get_major_ticks():\n",
    "        tick.label.set_fontsize(fs_tick)\n",
    "    for tick in inset.xaxis.get_major_ticks():\n",
    "        tick.label.set_fontsize(fs_tick-2)\n",
    "    for tick in par1.yaxis.get_major_ticks():\n",
    "        tick.label2.set_fontsize(fs_tick)\n",
    "\n",
    "    plt.savefig(figure_name,bbox_inches='tight')\n",
    "    return \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "CH4_indx = Header.index('CH4')\n",
    "O2_indx = Header.index('O2')\n",
    "CO_indx = Header.index('CO')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "info={}\n",
    "info['label1'] = {'label':'Temperature','units':' [K]'}\n",
    "info['label2'] = {'label': 'CH4','units':' Mass Fraction'}\n",
    "info['label3'] = {'label': 'O2','units':'  Mass Fraction'}\n",
    "info['label4'] = {'label': 'CO','units':'  Mass Fraction'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "info['loc_x'] = 0.45\n",
    "info['loc_y'] = 0.75\n",
    "info['xlim'] = [0.6,1.75]\n",
    "info['xlim2'] = [1.099,1.102]\n",
    "info['inset_x1'] = 0.55 \n",
    "info['inset_y1'] = 0.4\n",
    "info['inset_x2'] = 0.3\n",
    "info['inset_y2'] = 0.4\n",
    "\n",
    "x  = solTchem[:,1]\n",
    "y1 = solTchem[:,5]\n",
    "y2 = solTchem[:,CH4_indx]\n",
    "y3 = solTchem[:,O2_indx]\n",
    "y4 = solTchem[:,CO_indx]\n",
    "makefigure(x, y1, y2, y3, y4, info, fs_label=16, fs_tick=14, figure_name='TempMassFraction2.pdf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "info={}\n",
    "info['label1'] = {'label':'Temperature','units':' [K]'}\n",
    "info['label2'] = {'label': 'OH','units':' Mass Fraction'}\n",
    "info['label3'] = {'label': 'H','units':'  Mass Fraction'}\n",
    "info['label4'] = {'label': 'H2','units':' Mass Fraction'}\n",
    "info['loc_x'] = 0.55\n",
    "info['loc_y'] = 0.55\n",
    "info['xlim'] = [0.7,1.5]\n",
    "info['xlim2'] = [1.099,1.102]\n",
    "info['inset_x1'] = 0.15 \n",
    "info['inset_y1'] = 0.35\n",
    "info['inset_x2'] = 0.3\n",
    "info['inset_y2'] = 0.4\n",
    "OH_indx = Header.index('OH')\n",
    "H_indx = Header.index('H')\n",
    "H2_indx = Header.index('H2')\n",
    "y1 = solTchem[:,5]\n",
    "y2 = solTchem[:,OH_indx]\n",
    "y3 = solTchem[:,H_indx]\n",
    "y4 = solTchem[:,H2_indx]\n",
    "makefigure(x, y1, y2, y3, y4, info, figure_name='TempMassFraction3.pdf')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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g3QH8jaRZwN8AP46IPaVlrwUey6ieHcCLDGwNHcDAVlNm/PgJy9zZZ/e//uIX9543s5rSBtLfA0cBvwAOBi6oWPZekutILYuIXcAmYFHVokXsfQ0rU24hWeauvrr+vJkNkCqQStdfuoG3AK+NiLsqFq+kgU4NkiZKmi1pdmn/3aX57tIqFwFLJJ0q6RBJK4CDgIvT7qNRbiFZ5k44of68mQ2giNSXZrLZobQAWFdj0eURsaS0zhnAp4FXkdyz9LcRcXO7a+vp6Ym+vr6hVzRLo9y77tOfhi98Id9azNpI0qaI6Gl5O4MFkqQPA/8eEb9roKgPA9dGxB9aLWw4SToeOH7mzJmn3X///XmXY52iHEjD/Eef2XDLKpDqnbL7FvC6BgrqKn3mta0WNdx8ys7MLH9DPX7iVElpnyzmmy3MzKxpQw0ddNqwVJGzilN2eZdiZjZq1Rvte0yT0x3D+Q/Igk/ZmZnlz6fZzMysEBxI+MZYM7MicCDhU3ZmZkXgQDIzs0JwIJm1mwdWNUslVSBJ6pa0zyDLxlaMQzci+RqSZc6jfZs1LG0L6UHgyEGWHVFaPmL5GpJlzqN9mzUsbSDVewbzPsCeOsvNRh+P9m3WsEEDSdJ+kl4nqTye3avL8xXTYcBHgMeHpVqzkaJydG+P9m2WSr2hgz5J8pyjKE3fG2Q90cDzkMxGHYeRWSr1Aun/AltJAuebwOeAB6rWeR64p+qBfWZmZg0bNJAi4hckjyxHUpA8G2nHcBU2nDy4qplZ/tI+wvzyTg0jcC87M7MiGLSFJOknDWwnIuIdGdRjZmajVL1rSGNIOjOUHQxMJbmutB04EJgBPAbc157yzMxstKh3DWlB+bWk9wIrgKMi4vaK9/8zcGVpmZmZWdPS3hh7AfAPlWEEEBG3ActIeuCZmZk1LW0gvQF4cpBlTwDunmY2GI9jZ5ZKI2PZ/fUgy/6a5LrSiOXBVS1zHlzVrGGKiKFXkj4EXAHcSzJiQ7lTwweANwInRcSVbaxzWPT09ERfX1/eZVgneMMb4Ne/7p+fORPuvz+/eszaSNKmiOhpdTtp70P6DvAXwFPAucA/l37+EfiLTggjs0x5cFWzhqVqIe31AWkMMBnYEREdNcq3W0iWKZUGyffgqtbhsmoh1bsPqaZSCD3R6o7NRg2HkVkqfoS5mZkVggPJzMwKwYFkZmaF0LGBJGmGpJ9IukfSLyVNzrsmMzMbXMOdGkaQy0mGO7pZ0iTgubwLMjOzwXVkIEk6DNgdETcDRISHYDAzK7hhP2Unab6kayQ9IikkLamxzhmSHpT0nKRNko5ucDdvAJ6R9ENJd0r6bCbFm5lZ2+RxDWkisAX4JPBs9UJJJ5I8zmI5cCSwAVgjqbtinS2DTNNKq4wFFgCfAN4CzJH0vnb+o8wG5XHszFIZ9lN2EXEdcB2ApFU1VjkLWBURl5TmPy7pWOB0kuGKiIhZQ+zmYWBTRGwr7edHwGzgBy3/A8zSqB5cFXyDrNkQCtXLTtI4YA6wtmrRWmBeA5v6ObC/pP0lCTgGuGeQfS6V1Cep78knB3vChlmDrr66/ryZDVCoQCIZI6+LZDTxSttJHp+eSkS8CJwNrAPuAnYA3x1k3ZUR0RMRPVOmTGmqaLMBPLiqWcOKFkhl1SO+qsZ79TcQsTYi/lNEHB4RZ0adUWT9PCTLXOXpOQ+uapZK0QJpB/AiA1tDBzCw1ZSZiLg2IpZOmjSpXbuw0cxhZJZKoQIpInYBm4BFVYsWkfS2awu3kMzM8pfHfUgTJc2WNLu0/+7SfLlb90XAEkmnSjpE0grgIODidtXkFpKZWf7yaCH1AHeWpglAb+n1ZwFKT5/9FHAesBl4G3BcuQt3O7iFZGaWv4afGNvJ/MRYy1T5ibH+jlmHy+qJsYW6hmRmZqOXAwmfsjMzKwIHEu7UYGZWBA4ks3Y7+eS8KzAbERxIZu1QGUJXXOFQMkvBgYSvIVkbrFlTf97MBnAg4WtI1gaLF9efN7MBHEhm7bB6df/rk07ae97ManIgmbWbw8gsFQcSvoZkZlYEDiR8DcnMrAgcSGZmVggOJDMzKwQHkpmZFYIDCXdqMDMrAgcS7tRgZlYEDiSzdjv77LwrMBsRHEhm7VAZQl/8okPJLAUHklk7XH11/XkzG8CBZNYOJ5xQf97MBnAgmbXDF77Q//rTn9573sxqciCZtZvDyCwVBxK+D8nMrAgcSPg+JDOzInAgmZlZITiQzMysEBxIZmZWCA4kMzMrBAeSmZkVggPJzMwKoWMDSdLhkjZXTM9Kem/eddkodPLJeVdgNiKMzbuAdomIu4HZAJL2BR4EfpxrUTZ6VIbQFVckP1evzqcWsxGiY1tIVd4D3BARf8q7EBsl1qypP29mA+QSSJLmS7pG0iOSQtKSGuucIelBSc9J2iTp6BZ2eSJwZQufN2vM4sX1581sgLxaSBOBLcAngWerF0o6EVgBLAeOBDYAayR1V6yzZZBpWtW29gOOAvwnqg2fytNzJ53k03VmKSgi8i1A2gmcGRGrKt67DbgrIk6reO9+4HsRcW6D2/8osCAiPjzI8qXAUoDu7u4527Zta/wfYVaLlPzM+Ttm1m6SNkVET6vbKdw1JEnjgDnA2qpFa4F5TWzyROA7gy2MiJUR0RMRPVOmTGli82ZmloXCBRIwGegCtle9vx2Y2siGJE0m6WlXt3edHz9hZpa/IgZSWfV5DtV4r/4GInZExIERsXuI9fz4CTOznBUxkHYALzKwNXQAA1tNZmbWIQoXSBGxC9gELKpatIikt13mfMrOzCx/ed2HNFHSbEmzSzV0l+bL3bovApZIOlXSIZJWAAcBF7ejHp+yMzPLX14tpB7gztI0Aegtvf4sQERcCXwKOA/YDLwNOC4i2tIn2y0kM7P85X4fUpH09PREX19f3mVYpyjfh3TIIXDPPfnWYtZGHXsfkllHOPTQ/tf33rv3vJnV5EDCp+ysDe67r/68mQ3gQMKdGqwNDj64/ryZDeBAMmuHymtGvoZklooDyazdHEZmqTiQ8DUkM7MicCDha0hmZkXgQDIzs0JwIJmZWSE4kPA1JDOzInAg4WtIZmZF4EAyM7NCcCCZtZvHsTNLxYFk1g4eXNWsYQ4k3KnB2sCDq5o1zIGEOzVYG3hwVbOGOZDM2uGee5JBVceM8eCqZimNzbsAs47lEDJriFtIZmZWCA4kMzMrBAeSmZkVggPJzMwKwYGE70MyMysCBxK+D8nMrAgUEXnXUBiSngS25V1HlcnAjryLGCF8rNLxcUrHxym9gyNi31Y34vuQKkTElLxrqCapLyJ68q5jJPCxSsfHKR0fp/Qk9WWxHZ+yMzOzQnAgmZlZITiQim9l3gWMID5W6fg4pePjlF4mx8qdGszMrBDcQjIzs0JwIJmZWSE4kMzMrBAcSDmTdIakByU9J2mTpKOHWP+vJG2W9GdJj0taLWnqcNWbB0nzJV0j6RFJIWlJis8cLukmSc+WPne+JA1Dublq9FhJWiDph5IeK/1O3SXpo8NUbm6a+Z2q+OwbJD0jaWcbSyyEJr97kvQpSb+S9Hzpd+vzafbnQMqRpBOBFcBy4EhgA7BGUvcg678V+BfgcuAw4L3AocAVw1JwfiYCW4BPAs8OtbKklwM/BrYDbwY+AfwP4Kw21lgUDR0rYB5wN/ABYBbwdWClpL9qW4XF0OhxAkDSOOA7wM1tqqtomjlOXwbOAM4GDgGOI+3xighPOU3AbcAlVe/dD1w4yPp/B2yreu+/ATvz/rcM4zHbCSwZYp3TgaeBCRXvnQc8Qqln6WiY0hyrQT73XeD7eddfxOMEfAX4FrBkNH3v0h4n4GBgN3BIM/twCyknpb+05gBrqxatJfmrtZafAa8qjU4uSZOBDwHXta/SEWkucEtEVP5Fdz1wEDAjl4pGlpcDf8i7iKKR9C7g3SQtbqvtPcBvgGMl/UbSVkmXSzogzYcdSPmZDHSRnFaqtB2oeU0oIjYCf0lyim4X8CQg4CPtK3NEmkrt41peZoOQ9G7gHfim0L1IehVwCXBKRDyTdz0F9jpgOskfykuAU4A3AtdKGjJvHEj5q74zWTXeSxZIhwJfBS4gaV0dS/If7DfaWeAIVeu41nrfSkrXKP8V+ERE3J53PQWzGvh6RNyadyEFNwYYTxLcN0fELSSh9BaS67lDftjysQN4kYF/sR/AwL/uy84Fbo+IL0XEXRFxPcnFw1MkTWtfqSPO49Q+rjD4sR3VJL0NWAOcHxFfz7ueAno78BlJL0h6AbgMeFlpfmnOtRXJY8ALEfH/Kt67H3gBqNlZq5IDKScRsQvYBCyqWrSIpLddLS8lCbFK5fmO79LcgI3A0ZJeUvHeIuBRYGsuFRWYpPkkYdQbEf8r73oK6nBgdsV0Pkmvs9nAVTnWVTQ/A8ZKen3Fe68jedTRkM+acyDl6yJgiaRTJR0iaQXJhfeLASR9W9K3K9a/FniPpNMlva50iuWrwB0R8dCwVz9MJE2UNFvSbJLf2e7SfHdp+YWSbqz4yL8CfwZWSZol6QTgHOCiKHUF6lSNHitJC0jC6GLgCklTS1Phng2WpUaPU0RsqZxIemzuKc13bAeQJr57NwB3AN+UdKSkI4FvkvQoHvqZSXl3JRztE8kpt63A8yQtpvkVy9YD66vW/zjwS5L/cB8j+c/3NXn/O9p8jBaQXPupnlaVlq8CtlZ95nCSex+eKx2nzzAKunw3eqxK87XW35pH/UU9TjU+v4RR0O27ye/eq0hajc8AT5B0wjowzf482reZmRWCT9mZmVkhOJDMzKwQHEhmZlYIDiQzMysEB5KZmRWCA8nMzArBgWSWQunhZENNW0vrriq/zluplnJ96xv87AsVnz21TSWa/YexeRdgNkLMrZr/AfALYFnFe8+Xfl5A8uDFongceB/JM6Ia8VaSkUOuzrwisxocSGYpRNUoz5KeB3ZUv19a94FhKyyd52vVOZSIuE3SjOzLMavNp+zMMlZ9yk7SjNJpr4+Vxv56XNIzklZLeqmkmZKul7RT0q8lDXi+laQjJF0j6Q+SnpX0M0lHt1DjRElfk/SQpOclbZd0g6Q3NrtNs1Y5kMyGz7kkp8A+QjJa9Ikkg5r+APh3ktNqdwHfknRY+UOS3kQyAvwrgdOA9wO/A26QNKfJWr4CfBDoJRkJ/WPAZmC/Jrdn1jKfsjMbPg9ERLn1c32phXMKycPMVgNI6gP+K/ABkkF0Ab4EPAS8PZLHliDpemAL8A/Ae5uoZS5wRURcVvHeD5rYjllm3EIyGz5rquZ/Vfp5ffmNSB5l8AQwDUDSBOAYktGT90gaK2ksyfOvbgDmN1nLz0keffI/JfVI6mpyO2aZcSCZDZ/q5+bsqvN++eGCrwS6SFpCu6umM4FXSGrme/xx4BvAR0nC6QlJX5H00ia2ZZYJn7IzK7Y/AnuAfwa+XWuFiNjT6EYjYifJNa1zJU0nOUX4eZIwPLvpas1a4EAyK7CI+JOkW4AjSJ4M3HD4pNjHNuDLkk4CZmW9fbO0HEhmxXcWydNvr5d0GckTcCcDbwK6IuKcRjcoaSNwDXA3sJPkOtURwOVZFW3WKAeSWcFFxB2S3kzyGPavApOAJ4E7SLqNN+Nmkm7f55D8P/Ab4G8j4qutV2zWHD/C3KyDSVoFLABmAhERLzbw2S5gBvBr4LSIuLQNJZr9B/eyM+t800l65d3Y4OeeJwkjs2HhFpJZByuNRTe5NPtMRNzXwGfnkNzvBLA1InZkW53Z3hxIZmZWCD5lZ2ZmheBAMjOzQnAgmZlZITiQzMysEBxIZmZWCP8f57u/qnX6QCoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.plot(x,solTchem[:,Header.index('dt')],'r.-')\n",
    "plt.yscale('log')\n",
    "plt.xlim([0.7,1.6])\n",
    "plt.ylabel('dt [s]',fontsize=16)\n",
    "plt.xlabel('Time [s]',fontsize=16)\n",
    "plt.xticks(fontsize=14)\n",
    "plt.yticks(fontsize=14)\n",
    "plt.savefig('dt.pdf',bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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